Abstract The Analytic Techniques and Technology Core (ATT) provides advanced data analytic services to Center investigators. It complements the functions of the Participant Recruitment and Management and Digital and Electrical Engineering Cores by concentrating on techniques and technologies for data analysis including the application of advanced statistical techniques. The Core assists Center investigators by (1) planning and conducting advanced statistical analyses using cutting-edge methods for the analysis of multivariate, longitudinal data; (2) training Center investigators in innovative advanced analytic techniques for integrative analyses, aggregating datasets, data documentation protocols, and data warehousing procedures; (3) assisting Center investigators with grant proposal preparation and final report preparation including write-up of methods, procedures, and results sections. The Core provides advanced statistical services to Center investigators such as random coefficient modeling, methods for the analysis of intra- and inter-individual change, best-methods for longitudinal analysis, and new approaches to structural equation modeling and other multivariate techniques. The Core provides timely access to a highly trained, broadly experienced statistician who can design, execute, and interpret advanced multivariate models well beyond the scope of statistical services provided by other units or otherwise available to individual investigators. The Core serves a key role by integrating participation recruitment protocols provided by the Participant Recruitment Core, and digital data collection technologies, provided by the Digital Electronics and Engineering Core, to ensure efficient, accurate, and innovative standards for data collection, documentation, analysis, and interpretation. The Core provides individualized desk-side training and Center-wide tutorials and demonstrations for Center investigators which serve as incubators to stimulate new lines of inquiry made possible by the availability of new analytic methods and techniques such as techniques for drawing causal inference from group-based trajectories, extending growth curve modeling to applications with binary variables, and making group comparisons with logit and probit models. These Core services are strategic and targeted to the data-analytic needs of Center investigators to enable them to move forward on current research projects and to develop new research extensions and collaborations.